Organizer:

Introduction

Genes contribute to the development and progression of disease and they also influence how individuals respond to medicines. At GlaxoSmithKline (GSK), we are conducting genetic and genomic research which will allow the medical community to accurately prescribe the right medicine for the right patient.

In genetics research studies often hundreds to thousands of genetic markers, together with many clinical measurements, are collected. Statistical tools are useful for separating ‘true’ genes from ‘false’ alarms.

Research Question:

For this case study, a genetic data set is generated based on a complex genetic model we developed at GSK. There are 500 predictors (483 genetic markers and 17 clinical covariates). The goal is to identify the ‘true’ predictors among the 500 variables and, at the same time, control the false discovery rate. Therefore, the objectives are:

Identify ‘true’ genes and clinical covariates

Control False Discovery (number of true X’s versus number of false X’s identified)